Research on Adaptive Sliding Mode Robust Control Algorithm of Manipulator Based on RBF Neural Network | |
Tian, Hua2; Liang, Yanbing1 | |
2020 | |
会议日期 | 2020-11-06 |
会议地点 | Shanghai, PEOPLES R CHINA |
关键词 | Sliding mode ControlAdaptive ControlNeural network ControlRBF Network |
DOI | 10.1109/CAC51589.2020.9327630 |
页码 | 4625-4629 |
英文摘要 | This paper proposes a new algorithm for manipulator system-an adaptive sliding mode robust control algorithm based on RBF neural network. Based on the traditional sliding mode control method, the RBF neural network is used to approximate the manipulator model information and external interference. We established the system model of the six-degree-of-freedom manipulator XIOPM developed by our research group. In order to verify the effectiveness and superiority of the algorithm in the simplest possible case, we took the models of the first two joints and performed it through MTALAB. The simulation results are consistent with our expectations. Compared with the movement of the manipulator under traditional sliding mode control, our method can not only make the actual output trajectory of the manipulator system converge to the desired trajectory at a relatively faster speed, but also reduce chattering to a large extent. The control algorithm reduce the disadvantages of traditional sliding mode control. Its good tracking performance and tracking accuracy make this manipulator system well controlled. |
产权排序 | 1 |
会议录 | 2020 CHINESE AUTOMATION CONGRESS (CAC 2020) |
语种 | 英语 |
ISSN号 | 2688-092X;2688-0938 |
ISBN号 | 978-1-7281-7687-1 |
WOS记录号 | WOS:000678697004130 |
内容类型 | 会议论文 |
源URL | [http://ir.opt.ac.cn/handle/181661/95058] |
专题 | 西安光学精密机械研究所_光电测量技术实验室 |
通讯作者 | Tian, Hua |
作者单位 | 1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian, Peoples R China 2.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Univ Chinese Acad Sci, Xian, Peoples R China |
推荐引用方式 GB/T 7714 | Tian, Hua,Liang, Yanbing. Research on Adaptive Sliding Mode Robust Control Algorithm of Manipulator Based on RBF Neural Network[C]. 见:. Shanghai, PEOPLES R CHINA. 2020-11-06. |
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